Classification of multi-class motor imagery with a novel hierarchical SVM algorithm for brain–computer interfaces

• Published in: Medical & biological engineering & computing Vol. 55; no. 10; pp. 1809 - 1818
• Main Authors: Dong, Enzeng, Li, Changhai, Li, Liting, Du, Shengzhi, Belkacem, Abdelkader Nasreddine, Chen, Chao
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2017; Springer Nature B.V
• Subjects: Algorithms; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Brain; Classification; Competition; Computer Applications; EEG; Electroencephalography; Emulation; Feature extraction; Human Physiology; Image classification; Imaging; Interfaces; Mental task performance; Original Article; Radiology; Support vector machines; Wavelet analysis; Motor imagery; Electroencephalography (EEG); Common spatial pattern; Hierarchical support vector machine (HSVM)

Pattern classification algorithm is the crucial step in developing brain–computer interface (BCI) applications. In this paper, a hierarchical support vector machine (HSVM) algorithm is proposed to address an EEG-based four-class motor imagery classification task. Wavelet packet transform is employed...